Families’ experiences with medical research for pediatric rare diseases : a qualitative ethnographic study of parents and children participating in clinical trials for Duchenne muscular dystrophy (DMD)
Bibliographic record
Abstract
The biopharmaceutical industry has recently expanded its focus on developing new cures for rare diseases. As a growing number of personalised genomic treatments are tested in clinical trials, there is uncertainty about how to account for patient perspectives, and how to measure functional changes reported by patients and caregivers. The illness experiences of patients and families are also being reshaped as they adopt roles as collaborative stakeholders and participants in clinical studies. This dissertation examines these changes using data from qualitative ethnographic research conducted with families of children with Duchenne muscular dystrophy, a progressive and fatal genetic disease diagnosed in boys. Canadian and American families were followed using semi-structured interviews and observational methods as they participated in clinical trials testing a genomic treatment for DMD, called ataluren (formerly known as PTC124). Ethnographic work was also carried out with physicians, patient-advocates, and other professionals engaged in clinical neuromuscular research. The dissertation contributes to scholarly understanding of families’ everyday experiences in the clinical trial, the significance and meaning of investigational treatments from the patient perspective, and the social context in which pharmaceutical development for rare diseases occurs. I show how genetic research is reconfiguring patient communities and altering moral sensibilities about treatment and care, by revealing “lucky mutations” and new axes of biosocial commonality and difference. I explore the paths families take to the clinical trial, and the “stories of waiting” they tell about their experience in it. Finally, I examine how families navigate the uncertainty and liminality of their experience as trial subjects. I discuss how the trial unsettles taken-for-granted social roles, constraining clinical relationships and leaving parents to construct the significance of an experimental treatment in the context of limited information. In so doing, parents assemble and tell “narratives of efficacy” while administering study-drug to their children, drawing on their observations and those made by others. Though parents’ narratives are often dismissed as mere anecdote, I suggest they also offer insight for developing more personalised approaches to clinical research and outcome measurement for rare diseases, by restoring focus on the nuance, idiosyncrasy, and context of families’ experiences with investigational treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.015 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".